Bayesian-Inference-Driven Model Parametrization and Model Selection for 2CLJQ Fluid Models. - Owen Madin; Simon Boothroyd; Richard A. Messerly; Josh Fass; John D. Chodera; Michael R. Shirts (J. Chem. Inf. Model., 2022)

Uncertainty-driven dynamics for active learning of interatomic potentials. - Maksim Kulichenko; Kipton Barros; Nicholas Lubbers; Ying Wai Li; Richard A. Messerly; Sergei Tretiak; Justin S. Smith; Benjamin T. Nebgen (Nat. Comput. Sci., 2023)

Improving Bond Dissociations of Reactive Machine Learning Potentials through Physics-Constrained Data Augmentation. - Luan G. F. dos Santos; Benjamin T. Nebgen; Alice E. A. Allen; Brenden W. Hamilton; Sakib Matin; Justin S. Smith; Richard A. Messerly (J. Chem. Inf. Model., 2025)

Including Physics-Informed Atomization Constraints in Neural Networks for Reactive Chemistry. - Shuhao Zhang; Michael Chigaev; Olexandr Isayev; Richard A. Messerly; Nicholas Lubbers (J. Chem. Inf. Model., 2025)